Intergenic and genic sequence lengths have opposite relationships with respect to gene expression.

Eukaryotic genomes are mostly composed of noncoding DNA whose role is still poorly understood. Studies in several organisms have shown correlations between the length of the intergenic and genic sequences of a gene and the expression of its corresponding mRNA transcript. Some studies have found a positive relationship between intergenic sequence length and expression diversity between tissues, and concluded that genes under greater regulatory control require more regulatory information in their intergenic sequences. Other reports found a negative relationship between expression level and gene length and the interpretation was that there is selection pressure for highly expressed genes to remain small. However, a correlation between gene sequence length and expression diversity, opposite to that observed for intergenic sequences, has also been reported, and to date there is no testable explanation for this observation. To shed light on these varied and sometimes conflicting results, we performed a thorough study of the relationships between sequence length and gene expression using cell-type (tissue) specific microarray data in Arabidopsis thaliana. We measured median gene expression across tissues (expression level), expression variability between tissues (expression pattern uniformity), and expression variability between replicates (expression noise). We found that intergenic (upstream and downstream) and genic (coding and noncoding) sequences have generally opposite relationships with respect to expression, whether it is tissue variability, median, or expression noise. To explain these results we propose a model, in which the lengths of the intergenic and genic sequences have opposite effects on the ability of the transcribed region of the gene to be epigenetically regulated for differential expression. These findings could shed light on the role and influence of noncoding sequences on gene expression.

Quantification of transcription factor expression from Arabidopsis images.

MOTIVATION: Confocal microscopy has long provided qualitative information for a variety of applications in molecular biology. Recent advances have led to extensive image datasets, which can now serve as new data sources to obtain quantitative gene expression information. In contrast to microarrays, which usually provide data for many genes at one time point, these image data provide us with expression information for only one gene, but with the advantage of high spatial and/or temporal resolution, which is often lostin microarray samples. RESULTS: We have developed a prototype for the automatic analysis of Arabidopsis confocal images, which show the expression of a single transcription factor by means of GFP reporter constructs. Using techniques from image registration, we are able to address inherent problems of non-rigid transformation and partial mapping, and obtain relative expression values for 13 different tissues in Arabidopsis roots. This provides quantitative information with high spatial resolution, which accurately represents the underlying expression values within the organism. We validate our approach on a data set of 122 images depicting expression patterns of 30 transcription factors, both in terms of registration accuracy, as well as correlation with cell-sorted microarray data. Approaches like this will be useful to lay the groundwork to reconstruct regulatory networks on the level of tissues or even individual cells. AVAILABILITY: Upon request from the authors.

Transcriptional and posttranscriptional regulation of transcription factor expression in Arabidopsis roots.

Understanding how the expression of transcription factor (TF) genes is modulated is essential for reconstructing gene regulatory networks. There is increasing evidence that sequences other than upstream noncoding can contribute to modulating gene expression, but how frequently they do so remains unclear. Here, we investigated the regulation of TFs expressed in a tissue-enriched manner in Arabidopsis roots. For 61 TFs, we created GFP reporter constructs driven by each TF's upstream noncoding sequence (including the 5'UTR) fused to the GFP reporter gene alone or together with the TF's coding sequence. We compared the visually detectable GFP patterns with endogenous mRNA expression patterns, as defined by a genome-wide microarray root expression map. An automated image analysis method for quantifying GFP signals in different tissues was developed and used to validate our visual comparison method. From these combined analyses, we found that (i) the upstream noncoding sequence was sufficient to recapitulate the mRNA expression pattern for 80% (35/44) of the TFs, and (ii) 25% of the TFs undergo posttranscriptional regulation via microRNA-mediated mRNA degradation (2/24) or via intercellular protein movement (6/24). The results suggest that, for Arabidopsis TFs, upstream noncoding sequences are major contributors to mRNA expression pattern establishment, but modulation of transcription factor protein expression pattern after transcription is relatively frequent. This study provides a systematic overview of regulation of TF expression at a cellular level.

Transcriptional profile of the Arabidopsis root quiescent center.

The self-renewal characteristics of stem cells render them vital engines of development. To better understand the molecular mechanisms that determine the properties of stem cells, transcript profiling was conducted on quiescent center (QC) cells from the Arabidopsis thaliana root meristem. The AGAMOUS-LIKE 42 (AGL42) gene, which encodes a MADS box transcription factor whose expression is enriched in the QC, was used to mark these cells. RNA was isolated from sorted cells, labeled, and hybridized to Affymetrix microarrays. Comparisons with digital in situ expression profiles of surrounding tissues identified a set of genes enriched in the QC. Promoter regions from a subset of transcription factors identified as enriched in the QC conferred expression in the QC. These studies demonstrated that it is possible to successfully isolate and profile a rare cell type in the plant. Mutations in all enriched transcription factor genes including AGL42 exhibited no detectable root phenotype, raising the possibility of a high degree of functional redundancy in the QC.